Estimation of Fixed Parameters in Negative Binomial Mixed Model Using Shrinkage Estimators
Publish place: The Journal of Data Science and Modeling، Vol: 1، Issue: 2
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JCSM-1-2_006
تاریخ نمایه سازی: 18 بهمن 1400
Abstract:
In this paper, we consider the problem of parameter estimation in {color{blue} negative binomial mixed model} when it is suspected that some of the fixed parameters may be restricted to a subspace via linear shrinkage, {color{blue} preliminary test}, shrinkage {color{blue} preliminary test}, shrinkage, and positive shrinkage estimators along with the unrestricted maximum likelihood and restricted estimators. The random effects are considered as nuisance parameters. We conduct a Monte Carlo simulation study to evaluate the performance of each estimator in the sense of simulated relative efficiency. The results of simulation study reveal that the proposed estimation strategies perform more better than {color{blue} the} maximum likelihood method. The proposed estimators are applied to a real dataset to appraise their performance.
Keywords:
Longitudinal Data , Monte Carlo simulation , Negative Binomial Mixed Model , Over-dispersion , Shrinkage Estimators
Authors
Zahra Zandi
Department of Statistics, University of Tabriz, Tabriz, Iran
Hossein Bevrani
Department of Statistics, University of Tabriz, Tabriz, Iran
Reza Arabi Belaghi
Department of Statistics, University of Tabriz, Tabriz, Iran